Some properties of a simple moving average when applied to forecasting a time series
UNSPECIFIED (1999) Some properties of a simple moving average when applied to forecasting a time series. JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 50 (12). pp. 1267-1271. ISSN 0160-5682Full text not available from this repository.
Simple (equally weighted) moving averages are frequently used to estimate the current level of a time series; with this value being projected as a forecast for future observations. A key measure of the effectiveness of the method is the sampling error of the estimator, which this paper defines in terms of characteristics of the data. This enables the optimal length of the average for any steady state model to be established and the lead time forecast error derived. A comparison of the performance of a simple moving average (SMA) with an exponentially weighted moving average (EWMA) is made. It is shown that, for a Steady state model, the variance of the forecast error is typically less than 3% higher than the appropriate EWMA. This relatively small difference may explain the inconclusive results from the empirical studies about the relative predictive performance of the two methods.
|Item Type:||Journal Article|
|Subjects:||H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management|
|Journal or Publication Title:||JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY|
|Number of Pages:||5|
|Page Range:||pp. 1267-1271|
Actions (login required)